To use incense we first have to instantiate an experiment loader that will enable us to query the database for specific runs.
| targets_type | iteration | autoencoder_type | batch_size | artifacts | |
|---|---|---|---|---|---|
| exp_id | |||||
| 9 | Mnist | False | normal_dim | 256 | {'history_autoencoder': Artifact(name=history_... |
| 10 | Mnist | False | normal_dim | 128 | {'history_autoencoder': Artifact(name=history_... |
| 11 | Mnist | False | normal_dim | 64 | {'history_autoencoder': Artifact(name=history_... |
| 12 | Mnist | False | normal_dim | 32 | {'history_autoencoder': Artifact(name=history_... |
| 13 | 10_Targets | False | normal_dim | 256 | {'history_autoencoder': Artifact(name=history_... |
| 14 | 10_Targets | False | normal_dim | 128 | {'history_autoencoder': Artifact(name=history_... |
| 15 | 10_Targets | False | normal_dim | 64 | {'history_autoencoder': Artifact(name=history_... |
| 16 | 10_Targets | False | normal_dim | 32 | {'history_autoencoder': Artifact(name=history_... |
| 70 | Noisy | False | normal_dim | 256 | {'history_autoencoder': Artifact(name=history_... |
| 71 | Noisy | False | normal_dim | 128 | {'history_autoencoder': Artifact(name=history_... |
| 72 | Noisy | False | normal_dim | 64 | {'history_autoencoder': Artifact(name=history_... |
| 73 | Noisy | False | normal_dim | 32 | {'history_autoencoder': Artifact(name=history_... |
| targets_type | iteration | autoencoder_type | batch_size | artifacts | sort | |
|---|---|---|---|---|---|---|
| exp_id | ||||||
| 13 | 10_Targets | False | normal_dim | 256 | {'history_autoencoder': Artifact(name=history_... | 0 |
| 14 | 10_Targets | False | normal_dim | 128 | {'history_autoencoder': Artifact(name=history_... | 1 |
| 15 | 10_Targets | False | normal_dim | 64 | {'history_autoencoder': Artifact(name=history_... | 2 |
| 16 | 10_Targets | False | normal_dim | 32 | {'history_autoencoder': Artifact(name=history_... | 3 |
| 9 | Mnist | False | normal_dim | 256 | {'history_autoencoder': Artifact(name=history_... | 4 |
| 10 | Mnist | False | normal_dim | 128 | {'history_autoencoder': Artifact(name=history_... | 5 |
| 11 | Mnist | False | normal_dim | 64 | {'history_autoencoder': Artifact(name=history_... | 6 |
| 12 | Mnist | False | normal_dim | 32 | {'history_autoencoder': Artifact(name=history_... | 7 |
| 70 | Noisy | False | normal_dim | 256 | {'history_autoencoder': Artifact(name=history_... | 8 |
| 71 | Noisy | False | normal_dim | 128 | {'history_autoencoder': Artifact(name=history_... | 9 |
| 72 | Noisy | False | normal_dim | 64 | {'history_autoencoder': Artifact(name=history_... | 10 |
| 73 | Noisy | False | normal_dim | 32 | {'history_autoencoder': Artifact(name=history_... | 11 |
Red best overall, and also best of subset. Bes means for accuracy max, rest min. Green best of subset.
predictions_df_0
| normal_dim 256 10_Targets | normal_dim 128 10_Targets | normal_dim 64 10_Targets | normal_dim 32 10_Targets | normal_dim 256 Mnist | normal_dim 128 Mnist | normal_dim 64 Mnist | normal_dim 32 Mnist | normal_dim 256 Noisy | normal_dim 128 Noisy | normal_dim 64 Noisy | normal_dim 32 Noisy | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 0.9815 | 0.9812 | 0.9823 | 0.9828 | 0.9702 | 0.9754 | 0.9788 | 0.9745 | 0.9623 | 0.964 | 0.9646 | 0.9626 |
| 1 | 0.979 | 0.9785 | 0.979 | 0.9808 | 0.9661 | 0.9715 | 0.9733 | 0.97 | 0.9516 | 0.9508 | 0.9509 | 0.9502 |
| 2 | 0.9787 | 0.9783 | 0.888 | 0.9798 | 0.9553 | 0.9628 | 0.9641 | 0.9619 | 0.9357 | 0.9347 | 0.9308 | 0.929 |
| 3 | 0.9787 | 0.9782 | 0.8866 | 0.9797 | 0.9383 | 0.9487 | 0.9474 | 0.9487 | 0.9179 | 0.9142 | 0.9072 | 0.9074 |
| 4 | 0.9787 | 0.9782 | 0.8866 | 0.9797 | 0.9137 | 0.9341 | 0.9255 | 0.9308 | 0.9036 | 0.896 | 0.8874 | 0.8886 |
| 5 | 0.9787 | 0.9782 | 0.8866 | 0.9797 | 0.889 | 0.9173 | 0.9028 | 0.9085 | 0.8915 | 0.8805 | 0.8694 | 0.869 |
| 6 | 0.9787 | 0.9782 | 0.8866 | 0.9797 | 0.8614 | 0.8962 | 0.8784 | 0.886 | 0.8793 | 0.8638 | 0.8518 | 0.8506 |
| 7 | 0.9787 | 0.9782 | 0.8866 | 0.9797 | 0.8336 | 0.8731 | 0.8543 | 0.8586 | 0.8676 | 0.849 | 0.836 | 0.8357 |
| normal_dim 256 10_Targets | normal_dim 128 10_Targets | normal_dim 64 10_Targets | normal_dim 32 10_Targets | normal_dim 256 Mnist | normal_dim 128 Mnist | normal_dim 64 Mnist | normal_dim 32 Mnist | normal_dim 256 Noisy | normal_dim 128 Noisy | normal_dim 64 Noisy | normal_dim 32 Noisy | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 0.406183 | 0.408179 | 0.407608 | 0.407474 | 0.024755 | 0.0234812 | 0.0269704 | 0.0282939 | 0.654313 | 0.654617 | 0.65577 | 0.656995 |
| 1 | 0.411457 | 0.412459 | 0.40965 | 0.411199 | 0.0367421 | 0.0336826 | 0.0382817 | 0.0413423 | 0.669885 | 0.670316 | 0.67213 | 0.674791 |
| 2 | 0.41221 | 0.412886 | 0.417009 | 0.411752 | 0.0519603 | 0.0463235 | 0.0523998 | 0.0571439 | 0.68408 | 0.684528 | 0.687386 | 0.691021 |
| 3 | 0.412308 | 0.41294 | 0.429275 | 0.411833 | 0.0691046 | 0.0604308 | 0.0680922 | 0.0742471 | 0.696456 | 0.696987 | 0.701096 | 0.705155 |
| 4 | 0.412308 | 0.412948 | 0.429394 | 0.411838 | 0.0870761 | 0.0752679 | 0.0847133 | 0.0917471 | 0.707273 | 0.707905 | 0.713419 | 0.717449 |
| 5 | 0.412308 | 0.412948 | 0.429395 | 0.411838 | 0.10516 | 0.0903165 | 0.101343 | 0.109174 | 0.716811 | 0.717543 | 0.724535 | 0.728261 |
| 6 | 0.412308 | 0.412948 | 0.429395 | 0.411838 | 0.122949 | 0.105218 | 0.117771 | 0.126145 | 0.725304 | 0.72611 | 0.734668 | 0.737908 |
| 7 | 0.412308 | 0.412948 | 0.429395 | 0.411838 | 0.140185 | 0.119773 | 0.133901 | 0.142931 | 0.732967 | 0.733786 | 0.743981 | 0.746582 |
| normal_dim 256 10_Targets | normal_dim 128 10_Targets | normal_dim 64 10_Targets | normal_dim 32 10_Targets | normal_dim 256 Mnist | normal_dim 128 Mnist | normal_dim 64 Mnist | normal_dim 32 Mnist | normal_dim 256 Noisy | normal_dim 128 Noisy | normal_dim 64 Noisy | normal_dim 32 Noisy | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 0.266431 | 0.266991 | 0.266421 | 0.266433 | 0.0497662 | 0.0480546 | 0.0517474 | 0.053198 | 0.376717 | 0.377687 | 0.379944 | 0.38026 |
| 1 | 0.267329 | 0.26793 | 0.267278 | 0.267102 | 0.0596667 | 0.0567758 | 0.0609211 | 0.0638463 | 0.38577 | 0.387085 | 0.38969 | 0.390295 |
| 2 | 0.26748 | 0.268034 | 0.272747 | 0.267218 | 0.0706438 | 0.0662624 | 0.071089 | 0.0751611 | 0.393433 | 0.395008 | 0.398159 | 0.398923 |
| 3 | 0.267497 | 0.268044 | 0.276986 | 0.267242 | 0.0819333 | 0.0759058 | 0.0814678 | 0.0863705 | 0.400082 | 0.401848 | 0.405675 | 0.406408 |
| 4 | 0.267496 | 0.268046 | 0.277031 | 0.267243 | 0.0930401 | 0.0853716 | 0.0917694 | 0.0971769 | 0.405892 | 0.407802 | 0.412383 | 0.412935 |
| 5 | 0.267496 | 0.268046 | 0.277031 | 0.267243 | 0.103745 | 0.0945215 | 0.101642 | 0.107506 | 0.41102 | 0.413017 | 0.418404 | 0.418679 |
| 6 | 0.267496 | 0.268046 | 0.277031 | 0.267243 | 0.113953 | 0.103277 | 0.111095 | 0.117276 | 0.415592 | 0.417621 | 0.423873 | 0.423788 |
| 7 | 0.267496 | 0.268046 | 0.277031 | 0.267243 | 0.12364 | 0.111615 | 0.120138 | 0.126696 | 0.41972 | 0.421727 | 0.42888 | 0.428383 |
predictions_df_10
| normal_dim 256 10_Targets | normal_dim 128 10_Targets | normal_dim 64 10_Targets | normal_dim 32 10_Targets | normal_dim 256 Mnist | normal_dim 128 Mnist | normal_dim 64 Mnist | normal_dim 32 Mnist | normal_dim 256 Noisy | normal_dim 128 Noisy | normal_dim 64 Noisy | normal_dim 32 Noisy | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 0.9702 | 0.9703 | 0.9725 | 0.9737 | 0.9437 | 0.9484 | 0.9534 | 0.9539 | 0.96 | 0.9592 | 0.9593 | 0.957 |
| 1 | 0.9673 | 0.967 | 0.9702 | 0.9728 | 0.9464 | 0.9546 | 0.9555 | 0.9558 | 0.9504 | 0.9504 | 0.9462 | 0.9441 |
| 2 | 0.9673 | 0.9669 | 0.8816 | 0.9723 | 0.9296 | 0.9418 | 0.9388 | 0.9416 | 0.9331 | 0.9326 | 0.9245 | 0.923 |
| 3 | 0.9673 | 0.9669 | 0.8796 | 0.9723 | 0.9044 | 0.9243 | 0.9139 | 0.9215 | 0.9137 | 0.9104 | 0.9057 | 0.8995 |
| 4 | 0.9673 | 0.9669 | 0.8796 | 0.9723 | 0.8749 | 0.903 | 0.8856 | 0.897 | 0.8973 | 0.8912 | 0.884 | 0.8801 |
| 5 | 0.9673 | 0.9669 | 0.8796 | 0.9723 | 0.8444 | 0.882 | 0.8544 | 0.8675 | 0.8844 | 0.8726 | 0.8647 | 0.8615 |
| 6 | 0.9673 | 0.9669 | 0.8796 | 0.9723 | 0.8123 | 0.8572 | 0.824 | 0.8355 | 0.8715 | 0.857 | 0.846 | 0.8453 |
| 7 | 0.9673 | 0.9669 | 0.8796 | 0.9723 | 0.7779 | 0.8327 | 0.7916 | 0.8049 | 0.8599 | 0.8424 | 0.8303 | 0.8314 |
| normal_dim 256 10_Targets | normal_dim 128 10_Targets | normal_dim 64 10_Targets | normal_dim 32 10_Targets | normal_dim 256 Mnist | normal_dim 128 Mnist | normal_dim 64 Mnist | normal_dim 32 Mnist | normal_dim 256 Noisy | normal_dim 128 Noisy | normal_dim 64 Noisy | normal_dim 32 Noisy | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 0.403668 | 0.40751 | 0.406656 | 0.40658 | 0.0502894 | 0.0501402 | 0.0531705 | 0.05323 | 0.654839 | 0.654999 | 0.655981 | 0.657194 |
| 1 | 0.411553 | 0.413656 | 0.410467 | 0.411666 | 0.0605093 | 0.0574014 | 0.0616628 | 0.0624245 | 0.670764 | 0.671248 | 0.672862 | 0.675631 |
| 2 | 0.412664 | 0.4141 | 0.417972 | 0.412485 | 0.0764619 | 0.0696777 | 0.0755108 | 0.0769719 | 0.68491 | 0.685501 | 0.68811 | 0.69195 |
| 3 | 0.41286 | 0.414108 | 0.430033 | 0.412557 | 0.0945023 | 0.0841159 | 0.0917475 | 0.0935722 | 0.697235 | 0.697954 | 0.70175 | 0.706033 |
| 4 | 0.412928 | 0.414108 | 0.430198 | 0.412559 | 0.113023 | 0.0994097 | 0.108795 | 0.111083 | 0.708013 | 0.708893 | 0.713984 | 0.718273 |
| 5 | 0.412937 | 0.414108 | 0.430199 | 0.412559 | 0.131267 | 0.114831 | 0.126082 | 0.128605 | 0.717541 | 0.718552 | 0.725043 | 0.729047 |
| 6 | 0.412937 | 0.414108 | 0.430199 | 0.412559 | 0.148966 | 0.13009 | 0.143144 | 0.145681 | 0.726042 | 0.727116 | 0.735079 | 0.738636 |
| 7 | 0.412937 | 0.414108 | 0.430199 | 0.412559 | 0.165997 | 0.144998 | 0.159629 | 0.161962 | 0.733677 | 0.73476 | 0.744282 | 0.747266 |
| normal_dim 256 10_Targets | normal_dim 128 10_Targets | normal_dim 64 10_Targets | normal_dim 32 10_Targets | normal_dim 256 Mnist | normal_dim 128 Mnist | normal_dim 64 Mnist | normal_dim 32 Mnist | normal_dim 256 Noisy | normal_dim 128 Noisy | normal_dim 64 Noisy | normal_dim 32 Noisy | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 0.266264 | 0.267398 | 0.266584 | 0.266509 | 0.0740602 | 0.0734446 | 0.0756389 | 0.0757986 | 0.379938 | 0.380751 | 0.382924 | 0.383183 |
| 1 | 0.26758 | 0.268586 | 0.267785 | 0.267449 | 0.0787871 | 0.076552 | 0.0796463 | 0.0805345 | 0.387009 | 0.388317 | 0.39081 | 0.391429 |
| 2 | 0.267778 | 0.268689 | 0.273215 | 0.267621 | 0.0879414 | 0.0836189 | 0.0875788 | 0.0891107 | 0.394199 | 0.395836 | 0.39883 | 0.399681 |
| 3 | 0.267818 | 0.268691 | 0.277408 | 0.267632 | 0.0983289 | 0.0920365 | 0.0969103 | 0.0988525 | 0.400671 | 0.402536 | 0.406154 | 0.407013 |
| 4 | 0.267845 | 0.268691 | 0.277468 | 0.267632 | 0.108826 | 0.100847 | 0.106535 | 0.108903 | 0.406393 | 0.408426 | 0.412746 | 0.413463 |
| 5 | 0.267846 | 0.268691 | 0.277468 | 0.267632 | 0.118998 | 0.109568 | 0.116135 | 0.118739 | 0.411474 | 0.413609 | 0.418693 | 0.419158 |
| 6 | 0.267846 | 0.268691 | 0.277468 | 0.267632 | 0.128729 | 0.118038 | 0.125465 | 0.128158 | 0.416019 | 0.418186 | 0.424077 | 0.424228 |
| 7 | 0.267846 | 0.268691 | 0.277468 | 0.267632 | 0.137978 | 0.126183 | 0.134364 | 0.137013 | 0.420109 | 0.422257 | 0.42901 | 0.428787 |
predictions_df_20
| normal_dim 256 10_Targets | normal_dim 128 10_Targets | normal_dim 64 10_Targets | normal_dim 32 10_Targets | normal_dim 256 Mnist | normal_dim 128 Mnist | normal_dim 64 Mnist | normal_dim 32 Mnist | normal_dim 256 Noisy | normal_dim 128 Noisy | normal_dim 64 Noisy | normal_dim 32 Noisy | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 0.9499 | 0.9568 | 0.9586 | 0.9586 | 0.9046 | 0.9067 | 0.9143 | 0.9191 | 0.9523 | 0.9536 | 0.9533 | 0.953 |
| 1 | 0.9485 | 0.9467 | 0.9547 | 0.9579 | 0.9156 | 0.9184 | 0.9199 | 0.9247 | 0.942 | 0.9426 | 0.9424 | 0.9404 |
| 2 | 0.9486 | 0.9462 | 0.8688 | 0.9571 | 0.8963 | 0.9077 | 0.8931 | 0.9081 | 0.9256 | 0.9242 | 0.9235 | 0.9196 |
| 3 | 0.9485 | 0.9462 | 0.8652 | 0.957 | 0.8658 | 0.8847 | 0.8622 | 0.8771 | 0.907 | 0.9028 | 0.8986 | 0.8981 |
| 4 | 0.9487 | 0.9462 | 0.8652 | 0.957 | 0.8282 | 0.8601 | 0.8249 | 0.8415 | 0.8912 | 0.883 | 0.8773 | 0.8758 |
| 5 | 0.9486 | 0.9462 | 0.8652 | 0.957 | 0.7921 | 0.836 | 0.7892 | 0.8057 | 0.878 | 0.8633 | 0.8564 | 0.8562 |
| 6 | 0.9486 | 0.9462 | 0.8652 | 0.957 | 0.7551 | 0.8082 | 0.7532 | 0.768 | 0.8646 | 0.8504 | 0.8371 | 0.8382 |
| 7 | 0.9486 | 0.9462 | 0.8652 | 0.957 | 0.7192 | 0.7785 | 0.7229 | 0.7368 | 0.8532 | 0.837 | 0.8201 | 0.821 |
| normal_dim 256 10_Targets | normal_dim 128 10_Targets | normal_dim 64 10_Targets | normal_dim 32 10_Targets | normal_dim 256 Mnist | normal_dim 128 Mnist | normal_dim 64 Mnist | normal_dim 32 Mnist | normal_dim 256 Noisy | normal_dim 128 Noisy | normal_dim 64 Noisy | normal_dim 32 Noisy | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 0.401566 | 0.407414 | 0.405025 | 0.405283 | 0.0789296 | 0.0810586 | 0.08523 | 0.0792877 | 0.655929 | 0.656125 | 0.656782 | 0.657778 |
| 1 | 0.412268 | 0.417075 | 0.41105 | 0.413413 | 0.0881912 | 0.0870752 | 0.0927642 | 0.0864279 | 0.672258 | 0.67298 | 0.674161 | 0.676794 |
| 2 | 0.414048 | 0.418045 | 0.41879 | 0.414256 | 0.10477 | 0.0998136 | 0.107025 | 0.100372 | 0.686313 | 0.687228 | 0.689412 | 0.693121 |
| 3 | 0.41427 | 0.418083 | 0.43078 | 0.414337 | 0.123663 | 0.114859 | 0.123549 | 0.116679 | 0.698515 | 0.699598 | 0.70297 | 0.707205 |
| 4 | 0.414344 | 0.418083 | 0.430994 | 0.414352 | 0.142811 | 0.130555 | 0.14087 | 0.133741 | 0.709182 | 0.710464 | 0.71514 | 0.719427 |
| 5 | 0.414371 | 0.418083 | 0.430995 | 0.414352 | 0.161364 | 0.146262 | 0.158243 | 0.150554 | 0.718586 | 0.720065 | 0.726134 | 0.73016 |
| 6 | 0.414374 | 0.418083 | 0.430995 | 0.414352 | 0.179078 | 0.161695 | 0.17533 | 0.167263 | 0.726985 | 0.72859 | 0.736191 | 0.739734 |
| 7 | 0.414373 | 0.418083 | 0.430995 | 0.414352 | 0.195942 | 0.176663 | 0.191698 | 0.183023 | 0.734581 | 0.736229 | 0.745468 | 0.748364 |
| normal_dim 256 10_Targets | normal_dim 128 10_Targets | normal_dim 64 10_Targets | normal_dim 32 10_Targets | normal_dim 256 Mnist | normal_dim 128 Mnist | normal_dim 64 Mnist | normal_dim 32 Mnist | normal_dim 256 Noisy | normal_dim 128 Noisy | normal_dim 64 Noisy | normal_dim 32 Noisy | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 0.266632 | 0.268568 | 0.266769 | 0.266817 | 0.096705 | 0.0977197 | 0.099211 | 0.0954676 | 0.383635 | 0.384419 | 0.386474 | 0.386508 |
| 1 | 0.268284 | 0.270632 | 0.26824 | 0.268425 | 0.0986812 | 0.0982424 | 0.10099 | 0.0974408 | 0.388652 | 0.390058 | 0.392378 | 0.392812 |
| 2 | 0.268581 | 0.270878 | 0.273627 | 0.268597 | 0.106619 | 0.104053 | 0.107727 | 0.104377 | 0.395267 | 0.397107 | 0.399916 | 0.400614 |
| 3 | 0.268611 | 0.27088 | 0.277828 | 0.268615 | 0.116406 | 0.111715 | 0.116148 | 0.113008 | 0.401489 | 0.40362 | 0.407036 | 0.407791 |
| 4 | 0.268622 | 0.27088 | 0.277901 | 0.268621 | 0.126506 | 0.119959 | 0.125183 | 0.122126 | 0.407064 | 0.409393 | 0.413511 | 0.414143 |
| 5 | 0.268631 | 0.27088 | 0.277901 | 0.268621 | 0.136323 | 0.128257 | 0.134276 | 0.131077 | 0.412038 | 0.414495 | 0.419383 | 0.419772 |
| 6 | 0.26863 | 0.27088 | 0.277901 | 0.268621 | 0.145686 | 0.136368 | 0.143177 | 0.139941 | 0.416499 | 0.419018 | 0.424754 | 0.424806 |
| 7 | 0.26863 | 0.27088 | 0.277901 | 0.268621 | 0.154558 | 0.144223 | 0.151683 | 0.148283 | 0.420546 | 0.423061 | 0.429686 | 0.429347 |
predictions_df_30
| normal_dim 256 10_Targets | normal_dim 128 10_Targets | normal_dim 64 10_Targets | normal_dim 32 10_Targets | normal_dim 256 Mnist | normal_dim 128 Mnist | normal_dim 64 Mnist | normal_dim 32 Mnist | normal_dim 256 Noisy | normal_dim 128 Noisy | normal_dim 64 Noisy | normal_dim 32 Noisy | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 0.9211 | 0.9291 | 0.9324 | 0.9402 | 0.8484 | 0.8502 | 0.8554 | 0.8666 | 0.9482 | 0.9476 | 0.9488 | 0.9443 |
| 1 | 0.9209 | 0.9148 | 0.9279 | 0.941 | 0.8644 | 0.8687 | 0.862 | 0.8772 | 0.9404 | 0.9381 | 0.9383 | 0.9336 |
| 2 | 0.9209 | 0.9137 | 0.8489 | 0.9398 | 0.8443 | 0.856 | 0.8318 | 0.8577 | 0.9233 | 0.9164 | 0.9157 | 0.9127 |
| 3 | 0.9209 | 0.9136 | 0.8432 | 0.9395 | 0.8096 | 0.8276 | 0.7894 | 0.8196 | 0.9065 | 0.8974 | 0.8938 | 0.8907 |
| 4 | 0.9207 | 0.9136 | 0.8432 | 0.9395 | 0.7711 | 0.8001 | 0.7464 | 0.7771 | 0.8883 | 0.878 | 0.8711 | 0.869 |
| 5 | 0.9207 | 0.9136 | 0.8432 | 0.9395 | 0.7313 | 0.768 | 0.7085 | 0.7329 | 0.8737 | 0.8598 | 0.8522 | 0.8489 |
| 6 | 0.9207 | 0.9136 | 0.8432 | 0.9395 | 0.6921 | 0.7365 | 0.67 | 0.6965 | 0.8631 | 0.843 | 0.8338 | 0.829 |
| 7 | 0.9207 | 0.9136 | 0.8432 | 0.9395 | 0.6531 | 0.7059 | 0.6299 | 0.6613 | 0.8518 | 0.8294 | 0.8155 | 0.813 |
| normal_dim 256 10_Targets | normal_dim 128 10_Targets | normal_dim 64 10_Targets | normal_dim 32 10_Targets | normal_dim 256 Mnist | normal_dim 128 Mnist | normal_dim 64 Mnist | normal_dim 32 Mnist | normal_dim 256 Noisy | normal_dim 128 Noisy | normal_dim 64 Noisy | normal_dim 32 Noisy | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 0.39972 | 0.408342 | 0.405548 | 0.404226 | 0.11174 | 0.116974 | 0.121919 | 0.107334 | 0.657462 | 0.657374 | 0.65801 | 0.658766 |
| 1 | 0.415414 | 0.423196 | 0.415446 | 0.414941 | 0.121169 | 0.123135 | 0.129149 | 0.113681 | 0.67426 | 0.674851 | 0.676048 | 0.678462 |
| 2 | 0.417902 | 0.424844 | 0.423254 | 0.41642 | 0.138609 | 0.136851 | 0.143653 | 0.127756 | 0.688287 | 0.689122 | 0.691391 | 0.694824 |
| 3 | 0.418224 | 0.424972 | 0.434709 | 0.416567 | 0.158104 | 0.152708 | 0.160389 | 0.143935 | 0.700306 | 0.701341 | 0.704828 | 0.708781 |
| 4 | 0.418263 | 0.424999 | 0.435005 | 0.416568 | 0.177548 | 0.168921 | 0.177692 | 0.161158 | 0.710796 | 0.712037 | 0.716848 | 0.720966 |
| 5 | 0.418301 | 0.425009 | 0.435006 | 0.416569 | 0.196173 | 0.184893 | 0.194883 | 0.177825 | 0.720063 | 0.721488 | 0.727718 | 0.731778 |
| 6 | 0.4183 | 0.425009 | 0.435006 | 0.416569 | 0.213725 | 0.200461 | 0.211572 | 0.194125 | 0.728359 | 0.729941 | 0.737603 | 0.741435 |
| 7 | 0.4183 | 0.425009 | 0.435006 | 0.416569 | 0.230168 | 0.215349 | 0.22762 | 0.208939 | 0.735867 | 0.737552 | 0.746705 | 0.750084 |
| normal_dim 256 10_Targets | normal_dim 128 10_Targets | normal_dim 64 10_Targets | normal_dim 32 10_Targets | normal_dim 256 Mnist | normal_dim 128 Mnist | normal_dim 64 Mnist | normal_dim 32 Mnist | normal_dim 256 Noisy | normal_dim 128 Noisy | normal_dim 64 Noisy | normal_dim 32 Noisy | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 0.267842 | 0.270801 | 0.26843 | 0.267434 | 0.120138 | 0.12272 | 0.122911 | 0.114469 | 0.388009 | 0.388508 | 0.39054 | 0.390494 |
| 1 | 0.270285 | 0.274225 | 0.270686 | 0.269442 | 0.120797 | 0.122337 | 0.123651 | 0.115008 | 0.390834 | 0.392081 | 0.394363 | 0.39468 |
| 2 | 0.270678 | 0.274635 | 0.275886 | 0.269776 | 0.127935 | 0.127603 | 0.129675 | 0.121056 | 0.396839 | 0.398588 | 0.401352 | 0.401922 |
| 3 | 0.270731 | 0.274659 | 0.279969 | 0.269816 | 0.137168 | 0.134829 | 0.137495 | 0.128866 | 0.40276 | 0.40483 | 0.408219 | 0.408853 |
| 4 | 0.270733 | 0.274666 | 0.280069 | 0.269817 | 0.146806 | 0.142702 | 0.145924 | 0.137546 | 0.408139 | 0.410429 | 0.414531 | 0.41511 |
| 5 | 0.270737 | 0.274668 | 0.280069 | 0.269817 | 0.156183 | 0.15066 | 0.154464 | 0.14603 | 0.41297 | 0.415401 | 0.420279 | 0.420725 |
| 6 | 0.270737 | 0.274668 | 0.280069 | 0.269817 | 0.165086 | 0.158488 | 0.162817 | 0.154366 | 0.417325 | 0.419855 | 0.425514 | 0.425768 |
| 7 | 0.270737 | 0.274668 | 0.280069 | 0.269817 | 0.173449 | 0.165975 | 0.170892 | 0.161958 | 0.421281 | 0.423857 | 0.430333 | 0.430287 |
predictions_df_40
| normal_dim 256 10_Targets | normal_dim 128 10_Targets | normal_dim 64 10_Targets | normal_dim 32 10_Targets | normal_dim 256 Mnist | normal_dim 128 Mnist | normal_dim 64 Mnist | normal_dim 32 Mnist | normal_dim 256 Noisy | normal_dim 128 Noisy | normal_dim 64 Noisy | normal_dim 32 Noisy | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 0.8753 | 0.8893 | 0.8957 | 0.9101 | 0.7812 | 0.7859 | 0.7806 | 0.8153 | 0.9353 | 0.9358 | 0.9319 | 0.9333 |
| 1 | 0.8747 | 0.8653 | 0.8894 | 0.9099 | 0.8046 | 0.8008 | 0.788 | 0.8272 | 0.9279 | 0.9241 | 0.9224 | 0.9264 |
| 2 | 0.8746 | 0.8637 | 0.8157 | 0.9088 | 0.7735 | 0.7796 | 0.7519 | 0.7913 | 0.9086 | 0.9056 | 0.9029 | 0.9019 |
| 3 | 0.8746 | 0.8635 | 0.8089 | 0.9087 | 0.7385 | 0.7467 | 0.7113 | 0.7464 | 0.8911 | 0.8853 | 0.8794 | 0.8794 |
| 4 | 0.8744 | 0.8635 | 0.8089 | 0.9087 | 0.6943 | 0.7145 | 0.6656 | 0.7029 | 0.8731 | 0.8642 | 0.8552 | 0.8557 |
| 5 | 0.8744 | 0.8635 | 0.8089 | 0.9087 | 0.6506 | 0.6765 | 0.6273 | 0.6593 | 0.8572 | 0.8453 | 0.8349 | 0.8365 |
| 6 | 0.8744 | 0.8635 | 0.8089 | 0.9087 | 0.6152 | 0.6404 | 0.594 | 0.6236 | 0.8454 | 0.8291 | 0.8164 | 0.8202 |
| 7 | 0.8744 | 0.8635 | 0.8089 | 0.9087 | 0.5783 | 0.6099 | 0.5583 | 0.5879 | 0.8334 | 0.8166 | 0.7994 | 0.8057 |
| normal_dim 256 10_Targets | normal_dim 128 10_Targets | normal_dim 64 10_Targets | normal_dim 32 10_Targets | normal_dim 256 Mnist | normal_dim 128 Mnist | normal_dim 64 Mnist | normal_dim 32 Mnist | normal_dim 256 Noisy | normal_dim 128 Noisy | normal_dim 64 Noisy | normal_dim 32 Noisy | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 0.398473 | 0.409486 | 0.405093 | 0.401478 | 0.14846 | 0.157898 | 0.162714 | 0.138039 | 0.659447 | 0.659365 | 0.659623 | 0.660434 |
| 1 | 0.419404 | 0.431752 | 0.421153 | 0.417776 | 0.158797 | 0.16522 | 0.16925 | 0.143112 | 0.676798 | 0.677446 | 0.678267 | 0.680678 |
| 2 | 0.423355 | 0.434253 | 0.429555 | 0.420008 | 0.177164 | 0.180584 | 0.183297 | 0.156712 | 0.69081 | 0.691768 | 0.693695 | 0.697138 |
| 3 | 0.4241 | 0.434428 | 0.440935 | 0.420237 | 0.197046 | 0.19751 | 0.199288 | 0.172501 | 0.702673 | 0.703959 | 0.707071 | 0.711045 |
| 4 | 0.424197 | 0.434451 | 0.441425 | 0.420242 | 0.216432 | 0.214307 | 0.215952 | 0.188673 | 0.713018 | 0.714634 | 0.719018 | 0.723076 |
| 5 | 0.424226 | 0.434451 | 0.441435 | 0.420242 | 0.234741 | 0.230496 | 0.232245 | 0.204733 | 0.72216 | 0.724037 | 0.72983 | 0.733607 |
| 6 | 0.424226 | 0.434451 | 0.441435 | 0.420242 | 0.251845 | 0.245859 | 0.247871 | 0.22013 | 0.730337 | 0.732413 | 0.739692 | 0.742942 |
| 7 | 0.424226 | 0.434451 | 0.441435 | 0.420242 | 0.267764 | 0.260389 | 0.262877 | 0.23505 | 0.737745 | 0.739952 | 0.748713 | 0.751345 |
| normal_dim 256 10_Targets | normal_dim 128 10_Targets | normal_dim 64 10_Targets | normal_dim 32 10_Targets | normal_dim 256 Mnist | normal_dim 128 Mnist | normal_dim 64 Mnist | normal_dim 32 Mnist | normal_dim 256 Noisy | normal_dim 128 Noisy | normal_dim 64 Noisy | normal_dim 32 Noisy | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 0.269725 | 0.274089 | 0.270518 | 0.268207 | 0.144321 | 0.149093 | 0.147213 | 0.133752 | 0.393013 | 0.393415 | 0.395335 | 0.395305 |
| 1 | 0.273146 | 0.279165 | 0.274277 | 0.271264 | 0.144703 | 0.14877 | 0.146961 | 0.13298 | 0.393505 | 0.394711 | 0.39682 | 0.397065 |
| 2 | 0.273808 | 0.279828 | 0.279328 | 0.271766 | 0.151463 | 0.154175 | 0.152197 | 0.138041 | 0.398764 | 0.400553 | 0.403112 | 0.403616 |
| 3 | 0.273946 | 0.279873 | 0.283497 | 0.271827 | 0.160222 | 0.161354 | 0.159135 | 0.145039 | 0.404331 | 0.406513 | 0.409697 | 0.41026 |
| 4 | 0.273955 | 0.279874 | 0.283655 | 0.271828 | 0.169336 | 0.169014 | 0.166814 | 0.152664 | 0.409504 | 0.411955 | 0.41587 | 0.416319 |
| 5 | 0.273957 | 0.279874 | 0.283657 | 0.271828 | 0.178181 | 0.176635 | 0.174573 | 0.160458 | 0.414207 | 0.41682 | 0.421542 | 0.421735 |
| 6 | 0.273957 | 0.279874 | 0.283657 | 0.271828 | 0.186554 | 0.18397 | 0.182121 | 0.168074 | 0.418475 | 0.421172 | 0.42673 | 0.426581 |
| 7 | 0.273957 | 0.279874 | 0.283657 | 0.271828 | 0.194395 | 0.190951 | 0.189483 | 0.175533 | 0.422371 | 0.42509 | 0.431463 | 0.430959 |
predictions_df_50
| normal_dim 256 10_Targets | normal_dim 128 10_Targets | normal_dim 64 10_Targets | normal_dim 32 10_Targets | normal_dim 256 Mnist | normal_dim 128 Mnist | normal_dim 64 Mnist | normal_dim 32 Mnist | normal_dim 256 Noisy | normal_dim 128 Noisy | normal_dim 64 Noisy | normal_dim 32 Noisy | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 0.8104 | 0.843 | 0.8465 | 0.8637 | 0.7102 | 0.7038 | 0.6837 | 0.7456 | 0.9231 | 0.9193 | 0.915 | 0.9178 |
| 1 | 0.8124 | 0.8109 | 0.835 | 0.8633 | 0.7185 | 0.715 | 0.6927 | 0.7507 | 0.9153 | 0.9117 | 0.9092 | 0.9101 |
| 2 | 0.8138 | 0.8083 | 0.7697 | 0.8624 | 0.6901 | 0.6885 | 0.6576 | 0.715 | 0.8945 | 0.8888 | 0.8862 | 0.8876 |
| 3 | 0.8137 | 0.8082 | 0.7614 | 0.8623 | 0.6518 | 0.6544 | 0.6096 | 0.6697 | 0.8753 | 0.8672 | 0.8625 | 0.8648 |
| 4 | 0.8135 | 0.8082 | 0.7613 | 0.8623 | 0.6091 | 0.6164 | 0.5704 | 0.6244 | 0.8545 | 0.8457 | 0.8368 | 0.8417 |
| 5 | 0.8135 | 0.8082 | 0.7613 | 0.8623 | 0.5705 | 0.585 | 0.5335 | 0.584 | 0.8388 | 0.8271 | 0.8157 | 0.8219 |
| 6 | 0.8135 | 0.8082 | 0.7613 | 0.8623 | 0.5306 | 0.5501 | 0.4981 | 0.5454 | 0.8235 | 0.8116 | 0.799 | 0.8043 |
| 7 | 0.8135 | 0.8082 | 0.7613 | 0.8623 | 0.5013 | 0.5231 | 0.4696 | 0.509 | 0.8113 | 0.7952 | 0.7836 | 0.7894 |
| normal_dim 256 10_Targets | normal_dim 128 10_Targets | normal_dim 64 10_Targets | normal_dim 32 10_Targets | normal_dim 256 Mnist | normal_dim 128 Mnist | normal_dim 64 Mnist | normal_dim 32 Mnist | normal_dim 256 Noisy | normal_dim 128 Noisy | normal_dim 64 Noisy | normal_dim 32 Noisy | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 0.399107 | 0.412362 | 0.407298 | 0.402069 | 0.188267 | 0.201783 | 0.208569 | 0.177367 | 0.662679 | 0.662416 | 0.662516 | 0.66272 |
| 1 | 0.427134 | 0.442528 | 0.428738 | 0.425446 | 0.199843 | 0.210575 | 0.213153 | 0.179138 | 0.680583 | 0.681436 | 0.681745 | 0.683465 |
| 2 | 0.43352 | 0.44571 | 0.437533 | 0.428058 | 0.219119 | 0.227662 | 0.225993 | 0.191304 | 0.69458 | 0.695877 | 0.697247 | 0.699886 |
| 3 | 0.434552 | 0.446022 | 0.448088 | 0.428288 | 0.239303 | 0.245776 | 0.241007 | 0.206327 | 0.706262 | 0.707904 | 0.710476 | 0.713526 |
| 4 | 0.434763 | 0.446023 | 0.448634 | 0.428298 | 0.258573 | 0.262979 | 0.256039 | 0.222903 | 0.716433 | 0.718417 | 0.722272 | 0.725372 |
| 5 | 0.434775 | 0.446023 | 0.448651 | 0.428298 | 0.276493 | 0.278979 | 0.271045 | 0.238192 | 0.725454 | 0.727737 | 0.732927 | 0.735813 |
| 6 | 0.434776 | 0.446023 | 0.448651 | 0.428298 | 0.292947 | 0.293865 | 0.285361 | 0.253124 | 0.733536 | 0.736051 | 0.742591 | 0.745091 |
| 7 | 0.434776 | 0.446023 | 0.448651 | 0.428298 | 0.30814 | 0.307676 | 0.298997 | 0.266585 | 0.74079 | 0.743516 | 0.751433 | 0.753417 |
| normal_dim 256 10_Targets | normal_dim 128 10_Targets | normal_dim 64 10_Targets | normal_dim 32 10_Targets | normal_dim 256 Mnist | normal_dim 128 Mnist | normal_dim 64 Mnist | normal_dim 32 Mnist | normal_dim 256 Noisy | normal_dim 128 Noisy | normal_dim 64 Noisy | normal_dim 32 Noisy | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 0.273311 | 0.278311 | 0.274183 | 0.270802 | 0.169088 | 0.175511 | 0.172673 | 0.156256 | 0.398883 | 0.399074 | 0.400948 | 0.400674 |
| 1 | 0.278325 | 0.2854 | 0.278733 | 0.275651 | 0.169797 | 0.175721 | 0.170949 | 0.153344 | 0.397079 | 0.398302 | 0.400182 | 0.400037 |
| 2 | 0.279431 | 0.286133 | 0.283535 | 0.276146 | 0.176476 | 0.181661 | 0.175267 | 0.157278 | 0.4015 | 0.403445 | 0.405709 | 0.405773 |
| 3 | 0.279604 | 0.28621 | 0.287424 | 0.276198 | 0.184892 | 0.189076 | 0.181465 | 0.163496 | 0.406656 | 0.409021 | 0.411898 | 0.411997 |
| 4 | 0.279643 | 0.286209 | 0.287614 | 0.276202 | 0.193521 | 0.196615 | 0.188107 | 0.170984 | 0.411577 | 0.414193 | 0.417807 | 0.4178 |
| 5 | 0.279641 | 0.286209 | 0.287617 | 0.276202 | 0.201823 | 0.203873 | 0.195059 | 0.178132 | 0.416094 | 0.418878 | 0.423263 | 0.42306 |
| 6 | 0.279641 | 0.286209 | 0.287617 | 0.276202 | 0.209588 | 0.210755 | 0.201787 | 0.185324 | 0.420222 | 0.423102 | 0.428268 | 0.427808 |
| 7 | 0.279641 | 0.286209 | 0.287617 | 0.276202 | 0.216819 | 0.217192 | 0.208311 | 0.191876 | 0.423984 | 0.426912 | 0.432879 | 0.432108 |
predictions_df_60
| normal_dim 256 10_Targets | normal_dim 128 10_Targets | normal_dim 64 10_Targets | normal_dim 32 10_Targets | normal_dim 256 Mnist | normal_dim 128 Mnist | normal_dim 64 Mnist | normal_dim 32 Mnist | normal_dim 256 Noisy | normal_dim 128 Noisy | normal_dim 64 Noisy | normal_dim 32 Noisy | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 0.7325 | 0.771 | 0.776 | 0.8011 | 0.6279 | 0.6315 | 0.5911 | 0.6701 | 0.894 | 0.8908 | 0.897 | 0.8923 |
| 1 | 0.7312 | 0.7362 | 0.762 | 0.8056 | 0.6301 | 0.632 | 0.5976 | 0.6806 | 0.8907 | 0.8868 | 0.8897 | 0.8864 |
| 2 | 0.7315 | 0.7338 | 0.7047 | 0.802 | 0.5931 | 0.6025 | 0.5561 | 0.6393 | 0.8749 | 0.8673 | 0.8659 | 0.866 |
| 3 | 0.7314 | 0.7338 | 0.6957 | 0.8018 | 0.5556 | 0.5568 | 0.5132 | 0.5867 | 0.856 | 0.8473 | 0.8416 | 0.8418 |
| 4 | 0.7314 | 0.7338 | 0.6958 | 0.8019 | 0.5205 | 0.5232 | 0.4763 | 0.5415 | 0.8388 | 0.8236 | 0.8136 | 0.8211 |
| 5 | 0.7314 | 0.7338 | 0.6958 | 0.8019 | 0.485 | 0.4878 | 0.4473 | 0.5031 | 0.8222 | 0.8033 | 0.7926 | 0.8003 |
| 6 | 0.7314 | 0.7338 | 0.6958 | 0.8019 | 0.4497 | 0.4593 | 0.414 | 0.4712 | 0.8088 | 0.7879 | 0.7766 | 0.781 |
| 7 | 0.7314 | 0.7338 | 0.6958 | 0.8019 | 0.4253 | 0.4373 | 0.3911 | 0.4435 | 0.7956 | 0.7729 | 0.7589 | 0.7675 |
| normal_dim 256 10_Targets | normal_dim 128 10_Targets | normal_dim 64 10_Targets | normal_dim 32 10_Targets | normal_dim 256 Mnist | normal_dim 128 Mnist | normal_dim 64 Mnist | normal_dim 32 Mnist | normal_dim 256 Noisy | normal_dim 128 Noisy | normal_dim 64 Noisy | normal_dim 32 Noisy | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 0.404246 | 0.415999 | 0.41066 | 0.403715 | 0.231558 | 0.247913 | 0.25725 | 0.218518 | 0.667022 | 0.666319 | 0.666325 | 0.666299 |
| 1 | 0.439251 | 0.454707 | 0.441453 | 0.43463 | 0.245325 | 0.257559 | 0.259574 | 0.216983 | 0.685609 | 0.686234 | 0.68646 | 0.688047 |
| 2 | 0.447135 | 0.458615 | 0.450368 | 0.438785 | 0.266171 | 0.275057 | 0.270565 | 0.226807 | 0.699624 | 0.700893 | 0.702237 | 0.704688 |
| 3 | 0.448309 | 0.458932 | 0.460154 | 0.43914 | 0.286896 | 0.292735 | 0.283902 | 0.240673 | 0.711058 | 0.712878 | 0.715483 | 0.718264 |
| 4 | 0.44842 | 0.459006 | 0.460914 | 0.439176 | 0.30592 | 0.309111 | 0.297882 | 0.255848 | 0.721024 | 0.723327 | 0.727186 | 0.729996 |
| 5 | 0.448426 | 0.459007 | 0.460917 | 0.439178 | 0.323124 | 0.324244 | 0.311406 | 0.269943 | 0.729871 | 0.732602 | 0.737667 | 0.740295 |
| 6 | 0.448426 | 0.459007 | 0.460918 | 0.439179 | 0.338636 | 0.338282 | 0.324746 | 0.283565 | 0.7378 | 0.740881 | 0.747155 | 0.749456 |
| 7 | 0.448426 | 0.459007 | 0.460918 | 0.439179 | 0.35279 | 0.351148 | 0.337137 | 0.296849 | 0.745 | 0.748318 | 0.755824 | 0.75769 |
| normal_dim 256 10_Targets | normal_dim 128 10_Targets | normal_dim 64 10_Targets | normal_dim 32 10_Targets | normal_dim 256 Mnist | normal_dim 128 Mnist | normal_dim 64 Mnist | normal_dim 32 Mnist | normal_dim 256 Noisy | normal_dim 128 Noisy | normal_dim 64 Noisy | normal_dim 32 Noisy | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 0.278889 | 0.283678 | 0.279278 | 0.274848 | 0.194937 | 0.20206 | 0.198694 | 0.178885 | 0.405696 | 0.405674 | 0.407456 | 0.407166 |
| 1 | 0.285416 | 0.292182 | 0.286166 | 0.28113 | 0.196622 | 0.202466 | 0.195405 | 0.173956 | 0.401657 | 0.402645 | 0.404434 | 0.404289 |
| 2 | 0.286774 | 0.293094 | 0.290468 | 0.281981 | 0.203896 | 0.208399 | 0.198687 | 0.17643 | 0.405137 | 0.406953 | 0.409125 | 0.409213 |
| 3 | 0.286984 | 0.293162 | 0.294066 | 0.282047 | 0.212328 | 0.215372 | 0.203886 | 0.181793 | 0.409787 | 0.412143 | 0.414948 | 0.415057 |
| 4 | 0.286994 | 0.293173 | 0.294309 | 0.28205 | 0.220568 | 0.22231 | 0.209865 | 0.18834 | 0.414423 | 0.417128 | 0.420616 | 0.420642 |
| 5 | 0.286994 | 0.293173 | 0.29431 | 0.282049 | 0.228229 | 0.228985 | 0.21592 | 0.194715 | 0.41876 | 0.421692 | 0.425873 | 0.425743 |
| 6 | 0.286994 | 0.293173 | 0.29431 | 0.282049 | 0.235269 | 0.235262 | 0.222059 | 0.201088 | 0.422755 | 0.425808 | 0.430711 | 0.430364 |
| 7 | 0.286994 | 0.293173 | 0.29431 | 0.282049 | 0.241747 | 0.241094 | 0.227858 | 0.207406 | 0.426437 | 0.429525 | 0.435173 | 0.434545 |
predictions_df_70
| normal_dim 256 10_Targets | normal_dim 128 10_Targets | normal_dim 64 10_Targets | normal_dim 32 10_Targets | normal_dim 256 Mnist | normal_dim 128 Mnist | normal_dim 64 Mnist | normal_dim 32 Mnist | normal_dim 256 Noisy | normal_dim 128 Noisy | normal_dim 64 Noisy | normal_dim 32 Noisy | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 0.6424 | 0.6924 | 0.6892 | 0.7254 | 0.5432 | 0.5548 | 0.4819 | 0.5838 | 0.8528 | 0.8516 | 0.8563 | 0.8563 |
| 1 | 0.6419 | 0.656 | 0.6744 | 0.7251 | 0.5387 | 0.5416 | 0.483 | 0.5751 | 0.8578 | 0.8569 | 0.8557 | 0.8592 |
| 2 | 0.6402 | 0.6537 | 0.627 | 0.7218 | 0.5068 | 0.5073 | 0.4498 | 0.5368 | 0.8432 | 0.8376 | 0.8353 | 0.8382 |
| 3 | 0.6403 | 0.6535 | 0.6169 | 0.7215 | 0.4674 | 0.466 | 0.4212 | 0.495 | 0.8238 | 0.8165 | 0.8108 | 0.8121 |
| 4 | 0.6405 | 0.6535 | 0.6168 | 0.7215 | 0.4309 | 0.4353 | 0.4013 | 0.4569 | 0.8041 | 0.794 | 0.7886 | 0.7902 |
| 5 | 0.6405 | 0.6535 | 0.6168 | 0.7215 | 0.3974 | 0.4059 | 0.3765 | 0.4213 | 0.7907 | 0.7759 | 0.7668 | 0.7698 |
| 6 | 0.6404 | 0.6535 | 0.6168 | 0.7215 | 0.3705 | 0.3828 | 0.357 | 0.3957 | 0.778 | 0.7612 | 0.746 | 0.7532 |
| 7 | 0.6404 | 0.6535 | 0.6168 | 0.7215 | 0.3471 | 0.3588 | 0.3324 | 0.3718 | 0.7669 | 0.7474 | 0.727 | 0.7363 |
| normal_dim 256 10_Targets | normal_dim 128 10_Targets | normal_dim 64 10_Targets | normal_dim 32 10_Targets | normal_dim 256 Mnist | normal_dim 128 Mnist | normal_dim 64 Mnist | normal_dim 32 Mnist | normal_dim 256 Noisy | normal_dim 128 Noisy | normal_dim 64 Noisy | normal_dim 32 Noisy | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 0.409518 | 0.421532 | 0.415563 | 0.40436 | 0.274594 | 0.293222 | 0.30836 | 0.272889 | 0.673847 | 0.672533 | 0.672543 | 0.671785 |
| 1 | 0.450838 | 0.467912 | 0.454492 | 0.446293 | 0.289239 | 0.302874 | 0.306156 | 0.263908 | 0.693604 | 0.693438 | 0.693705 | 0.694767 |
| 2 | 0.461699 | 0.472804 | 0.464168 | 0.452165 | 0.310558 | 0.32057 | 0.313881 | 0.268382 | 0.70793 | 0.708225 | 0.709565 | 0.7119 |
| 3 | 0.4633 | 0.473207 | 0.473487 | 0.452887 | 0.331274 | 0.337965 | 0.324967 | 0.278823 | 0.719135 | 0.719926 | 0.722345 | 0.725396 |
| 4 | 0.463535 | 0.473229 | 0.474218 | 0.452936 | 0.349984 | 0.353662 | 0.336969 | 0.292706 | 0.72874 | 0.730099 | 0.733532 | 0.736902 |
| 5 | 0.463584 | 0.473244 | 0.474254 | 0.452937 | 0.366617 | 0.36777 | 0.348859 | 0.30636 | 0.737248 | 0.739174 | 0.743617 | 0.74701 |
| 6 | 0.463581 | 0.473244 | 0.474254 | 0.452937 | 0.381423 | 0.380516 | 0.36038 | 0.319061 | 0.744921 | 0.747312 | 0.752791 | 0.756019 |
| 7 | 0.463592 | 0.473244 | 0.474254 | 0.452937 | 0.394562 | 0.392138 | 0.371188 | 0.33078 | 0.7519 | 0.754596 | 0.76122 | 0.764074 |
| normal_dim 256 10_Targets | normal_dim 128 10_Targets | normal_dim 64 10_Targets | normal_dim 32 10_Targets | normal_dim 256 Mnist | normal_dim 128 Mnist | normal_dim 64 Mnist | normal_dim 32 Mnist | normal_dim 256 Noisy | normal_dim 128 Noisy | normal_dim 64 Noisy | normal_dim 32 Noisy | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 0.284931 | 0.289298 | 0.285147 | 0.279101 | 0.21964 | 0.227256 | 0.225593 | 0.207462 | 0.414186 | 0.413766 | 0.415476 | 0.415093 |
| 1 | 0.292974 | 0.299768 | 0.293712 | 0.288054 | 0.221828 | 0.22747 | 0.219427 | 0.198619 | 0.408246 | 0.408668 | 0.410494 | 0.410129 |
| 2 | 0.294863 | 0.300829 | 0.297768 | 0.289291 | 0.229319 | 0.233484 | 0.221105 | 0.198323 | 0.410834 | 0.412022 | 0.414168 | 0.414183 |
| 3 | 0.295097 | 0.300896 | 0.301319 | 0.289454 | 0.237613 | 0.240273 | 0.225095 | 0.201782 | 0.414908 | 0.416654 | 0.419298 | 0.41956 |
| 4 | 0.295118 | 0.3009 | 0.301547 | 0.289456 | 0.245487 | 0.246804 | 0.230037 | 0.20747 | 0.419106 | 0.421252 | 0.424477 | 0.42481 |
| 5 | 0.295127 | 0.300903 | 0.30156 | 0.289456 | 0.252637 | 0.252873 | 0.235174 | 0.213412 | 0.423103 | 0.425542 | 0.429389 | 0.429665 |
| 6 | 0.295126 | 0.300903 | 0.30156 | 0.289456 | 0.25907 | 0.258429 | 0.240343 | 0.219155 | 0.426848 | 0.429464 | 0.433979 | 0.434099 |
| 7 | 0.295126 | 0.300903 | 0.30156 | 0.289456 | 0.264794 | 0.263503 | 0.245247 | 0.224557 | 0.430332 | 0.433022 | 0.438247 | 0.438124 |
predictions_df_80
| normal_dim 256 10_Targets | normal_dim 128 10_Targets | normal_dim 64 10_Targets | normal_dim 32 10_Targets | normal_dim 256 Mnist | normal_dim 128 Mnist | normal_dim 64 Mnist | normal_dim 32 Mnist | normal_dim 256 Noisy | normal_dim 128 Noisy | normal_dim 64 Noisy | normal_dim 32 Noisy | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 0.5598 | 0.5938 | 0.6045 | 0.6312 | 0.4721 | 0.4641 | 0.3981 | 0.4879 | 0.8012 | 0.8067 | 0.7957 | 0.8013 |
| 1 | 0.5524 | 0.5583 | 0.5864 | 0.6295 | 0.4611 | 0.4453 | 0.394 | 0.4805 | 0.8048 | 0.8051 | 0.8031 | 0.8116 |
| 2 | 0.5525 | 0.5574 | 0.5507 | 0.6242 | 0.428 | 0.412 | 0.3734 | 0.4474 | 0.7898 | 0.7879 | 0.7795 | 0.7899 |
| 3 | 0.5525 | 0.5572 | 0.5419 | 0.6233 | 0.3923 | 0.3819 | 0.3518 | 0.409 | 0.7744 | 0.7685 | 0.7588 | 0.7653 |
| 4 | 0.5525 | 0.5572 | 0.5418 | 0.6232 | 0.358 | 0.354 | 0.3388 | 0.3857 | 0.7556 | 0.7484 | 0.7366 | 0.7438 |
| 5 | 0.5525 | 0.5572 | 0.5418 | 0.6232 | 0.3344 | 0.3333 | 0.3207 | 0.3563 | 0.7429 | 0.729 | 0.712 | 0.7236 |
| 6 | 0.5525 | 0.5572 | 0.5418 | 0.6232 | 0.3149 | 0.3138 | 0.3039 | 0.3312 | 0.7291 | 0.7106 | 0.6918 | 0.7045 |
| 7 | 0.5525 | 0.5572 | 0.5418 | 0.6231 | 0.2959 | 0.2998 | 0.2849 | 0.3122 | 0.7191 | 0.6955 | 0.6763 | 0.6912 |
| normal_dim 256 10_Targets | normal_dim 128 10_Targets | normal_dim 64 10_Targets | normal_dim 32 10_Targets | normal_dim 256 Mnist | normal_dim 128 Mnist | normal_dim 64 Mnist | normal_dim 32 Mnist | normal_dim 256 Noisy | normal_dim 128 Noisy | normal_dim 64 Noisy | normal_dim 32 Noisy | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 0.419228 | 0.431738 | 0.423274 | 0.412763 | 0.319946 | 0.341009 | 0.370053 | 0.34326 | 0.683892 | 0.682911 | 0.682496 | 0.679958 |
| 1 | 0.464674 | 0.485127 | 0.468674 | 0.464941 | 0.335582 | 0.349063 | 0.361413 | 0.322244 | 0.705116 | 0.705698 | 0.70505 | 0.704498 |
| 2 | 0.476911 | 0.490661 | 0.478811 | 0.473158 | 0.357098 | 0.365699 | 0.365443 | 0.317128 | 0.719751 | 0.72118 | 0.721379 | 0.72215 |
| 3 | 0.478827 | 0.491093 | 0.487049 | 0.473993 | 0.37729 | 0.381791 | 0.373641 | 0.322666 | 0.730758 | 0.73288 | 0.734113 | 0.735508 |
| 4 | 0.479061 | 0.49113 | 0.487817 | 0.474046 | 0.394982 | 0.39596 | 0.383487 | 0.334134 | 0.740104 | 0.742847 | 0.745071 | 0.746707 |
| 5 | 0.479091 | 0.49113 | 0.48785 | 0.474049 | 0.410116 | 0.408413 | 0.393202 | 0.345689 | 0.748375 | 0.751608 | 0.754888 | 0.756446 |
| 6 | 0.479098 | 0.49113 | 0.487851 | 0.474049 | 0.423287 | 0.419525 | 0.402857 | 0.357512 | 0.755801 | 0.759347 | 0.763788 | 0.765078 |
| 7 | 0.479098 | 0.49113 | 0.487851 | 0.474057 | 0.434632 | 0.429435 | 0.41203 | 0.368105 | 0.762519 | 0.766218 | 0.771913 | 0.772799 |
| normal_dim 256 10_Targets | normal_dim 128 10_Targets | normal_dim 64 10_Targets | normal_dim 32 10_Targets | normal_dim 256 Mnist | normal_dim 128 Mnist | normal_dim 64 Mnist | normal_dim 32 Mnist | normal_dim 256 Noisy | normal_dim 128 Noisy | normal_dim 64 Noisy | normal_dim 32 Noisy | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 0.292446 | 0.297199 | 0.292244 | 0.286975 | 0.245538 | 0.25351 | 0.257629 | 0.243098 | 0.424318 | 0.424194 | 0.425794 | 0.424643 |
| 1 | 0.300931 | 0.309245 | 0.301885 | 0.298563 | 0.248221 | 0.252652 | 0.247362 | 0.228293 | 0.416847 | 0.417696 | 0.419164 | 0.417822 |
| 2 | 0.303023 | 0.310386 | 0.305633 | 0.300316 | 0.255947 | 0.258143 | 0.247326 | 0.223467 | 0.418508 | 0.420294 | 0.421883 | 0.420916 |
| 3 | 0.303308 | 0.310471 | 0.308676 | 0.300544 | 0.263993 | 0.264242 | 0.249984 | 0.224517 | 0.422012 | 0.424386 | 0.426409 | 0.42571 |
| 4 | 0.303349 | 0.310479 | 0.308921 | 0.30056 | 0.271218 | 0.269906 | 0.253812 | 0.228922 | 0.425803 | 0.428543 | 0.431158 | 0.430542 |
| 5 | 0.303353 | 0.310479 | 0.308933 | 0.300561 | 0.277285 | 0.275044 | 0.257836 | 0.233653 | 0.429486 | 0.432443 | 0.435739 | 0.435058 |
| 6 | 0.303353 | 0.310479 | 0.308933 | 0.300561 | 0.282522 | 0.279676 | 0.262041 | 0.238841 | 0.432951 | 0.436005 | 0.440057 | 0.439192 |
| 7 | 0.303352 | 0.310479 | 0.308933 | 0.300565 | 0.287014 | 0.283811 | 0.266161 | 0.243621 | 0.436183 | 0.439222 | 0.444081 | 0.442969 |
predictions_df_90
| normal_dim 256 10_Targets | normal_dim 128 10_Targets | normal_dim 64 10_Targets | normal_dim 32 10_Targets | normal_dim 256 Mnist | normal_dim 128 Mnist | normal_dim 64 Mnist | normal_dim 32 Mnist | normal_dim 256 Noisy | normal_dim 128 Noisy | normal_dim 64 Noisy | normal_dim 32 Noisy | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 0.4652 | 0.4935 | 0.5065 | 0.5292 | 0.3957 | 0.3788 | 0.314 | 0.4017 | 0.7071 | 0.7092 | 0.7051 | 0.7246 |
| 1 | 0.461 | 0.4641 | 0.4886 | 0.5257 | 0.3832 | 0.3678 | 0.3143 | 0.3908 | 0.7148 | 0.7171 | 0.7135 | 0.7304 |
| 2 | 0.4608 | 0.4613 | 0.4613 | 0.5226 | 0.3501 | 0.3402 | 0.2969 | 0.3603 | 0.7032 | 0.7025 | 0.7004 | 0.7139 |
| 3 | 0.4609 | 0.4615 | 0.4539 | 0.5223 | 0.3198 | 0.3169 | 0.2837 | 0.3221 | 0.6893 | 0.6838 | 0.681 | 0.6914 |
| 4 | 0.4608 | 0.4616 | 0.4539 | 0.5222 | 0.2937 | 0.2955 | 0.2724 | 0.2999 | 0.675 | 0.6668 | 0.6613 | 0.6706 |
| 5 | 0.4608 | 0.4616 | 0.4539 | 0.5222 | 0.2748 | 0.2783 | 0.2565 | 0.2813 | 0.6632 | 0.6484 | 0.6415 | 0.654 |
| 6 | 0.4608 | 0.4616 | 0.4539 | 0.5222 | 0.2591 | 0.2617 | 0.2488 | 0.2639 | 0.6504 | 0.6314 | 0.6231 | 0.6381 |
| 7 | 0.4608 | 0.4616 | 0.4539 | 0.5222 | 0.2467 | 0.2532 | 0.235 | 0.2494 | 0.6422 | 0.6171 | 0.61 | 0.6224 |
| normal_dim 256 10_Targets | normal_dim 128 10_Targets | normal_dim 64 10_Targets | normal_dim 32 10_Targets | normal_dim 256 Mnist | normal_dim 128 Mnist | normal_dim 64 Mnist | normal_dim 32 Mnist | normal_dim 256 Noisy | normal_dim 128 Noisy | normal_dim 64 Noisy | normal_dim 32 Noisy | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 0.427204 | 0.437576 | 0.428068 | 0.421905 | 0.363935 | 0.385668 | 0.452028 | 0.436702 | 0.698825 | 0.697489 | 0.695876 | 0.691769 |
| 1 | 0.476592 | 0.499122 | 0.481791 | 0.48391 | 0.378551 | 0.390117 | 0.43303 | 0.39795 | 0.722475 | 0.722666 | 0.720736 | 0.718654 |
| 2 | 0.489934 | 0.505976 | 0.493166 | 0.49329 | 0.398947 | 0.404578 | 0.431089 | 0.37546 | 0.738333 | 0.739211 | 0.738099 | 0.737462 |
| 3 | 0.49196 | 0.506606 | 0.499699 | 0.494142 | 0.417719 | 0.419032 | 0.4349 | 0.371568 | 0.74965 | 0.751022 | 0.750958 | 0.751077 |
| 4 | 0.492389 | 0.506711 | 0.500468 | 0.494221 | 0.433353 | 0.431877 | 0.441362 | 0.379185 | 0.758926 | 0.760765 | 0.761751 | 0.762213 |
| 5 | 0.492441 | 0.506713 | 0.500503 | 0.494244 | 0.446655 | 0.443176 | 0.448601 | 0.389034 | 0.766981 | 0.7692 | 0.771273 | 0.771781 |
| 6 | 0.492441 | 0.506713 | 0.500503 | 0.494247 | 0.458022 | 0.453166 | 0.455825 | 0.39855 | 0.774132 | 0.776615 | 0.779837 | 0.780181 |
| 7 | 0.492441 | 0.506713 | 0.500503 | 0.494248 | 0.467886 | 0.461968 | 0.463112 | 0.407242 | 0.780542 | 0.783188 | 0.78762 | 0.787625 |
| normal_dim 256 10_Targets | normal_dim 128 10_Targets | normal_dim 64 10_Targets | normal_dim 32 10_Targets | normal_dim 256 Mnist | normal_dim 128 Mnist | normal_dim 64 Mnist | normal_dim 32 Mnist | normal_dim 256 Noisy | normal_dim 128 Noisy | normal_dim 64 Noisy | normal_dim 32 Noisy | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 0.299068 | 0.303071 | 0.298303 | 0.295683 | 0.270353 | 0.277639 | 0.299549 | 0.28932 | 0.437361 | 0.436989 | 0.437882 | 0.436412 |
| 1 | 0.307824 | 0.317106 | 0.309481 | 0.308793 | 0.27244 | 0.274363 | 0.282411 | 0.266012 | 0.429087 | 0.429509 | 0.430412 | 0.428378 |
| 2 | 0.309916 | 0.318569 | 0.313115 | 0.310672 | 0.279775 | 0.278832 | 0.279827 | 0.25328 | 0.430209 | 0.431449 | 0.432438 | 0.430719 |
| 3 | 0.310215 | 0.318698 | 0.315552 | 0.310885 | 0.286985 | 0.284098 | 0.280559 | 0.249867 | 0.433282 | 0.435039 | 0.436428 | 0.435013 |
| 4 | 0.310294 | 0.318725 | 0.315785 | 0.310915 | 0.292798 | 0.289071 | 0.282811 | 0.252309 | 0.436695 | 0.438777 | 0.440737 | 0.439462 |
| 5 | 0.310299 | 0.318725 | 0.315796 | 0.310923 | 0.297606 | 0.293576 | 0.285633 | 0.256194 | 0.440053 | 0.442291 | 0.444947 | 0.443667 |
| 6 | 0.310299 | 0.318725 | 0.315796 | 0.310925 | 0.301603 | 0.297615 | 0.288647 | 0.260149 | 0.443236 | 0.445504 | 0.448934 | 0.447544 |
| 7 | 0.310299 | 0.318725 | 0.315796 | 0.310925 | 0.305162 | 0.301156 | 0.291791 | 0.263878 | 0.446208 | 0.448432 | 0.452657 | 0.45107 |
predictions_df_100
| normal_dim 256 10_Targets | normal_dim 128 10_Targets | normal_dim 64 10_Targets | normal_dim 32 10_Targets | normal_dim 256 Mnist | normal_dim 128 Mnist | normal_dim 64 Mnist | normal_dim 32 Mnist | normal_dim 256 Noisy | normal_dim 128 Noisy | normal_dim 64 Noisy | normal_dim 32 Noisy | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 0.3784 | 0.4094 | 0.4158 | 0.4407 | 0.3254 | 0.3107 | 0.2505 | 0.3128 | 0.5857 | 0.5907 | 0.5885 | 0.6129 |
| 1 | 0.3693 | 0.3836 | 0.3974 | 0.4326 | 0.3141 | 0.2984 | 0.246 | 0.2982 | 0.597 | 0.6009 | 0.596 | 0.6273 |
| 2 | 0.3681 | 0.3827 | 0.3811 | 0.4304 | 0.288 | 0.2792 | 0.2367 | 0.2759 | 0.5942 | 0.5916 | 0.5907 | 0.6154 |
| 3 | 0.3684 | 0.3823 | 0.3729 | 0.43 | 0.2631 | 0.258 | 0.2292 | 0.2505 | 0.5812 | 0.5808 | 0.5753 | 0.5984 |
| 4 | 0.3683 | 0.3824 | 0.3729 | 0.4298 | 0.2384 | 0.2463 | 0.2215 | 0.2344 | 0.5686 | 0.5661 | 0.5623 | 0.5803 |
| 5 | 0.3682 | 0.3824 | 0.3729 | 0.4298 | 0.2252 | 0.2338 | 0.2085 | 0.2248 | 0.5569 | 0.5537 | 0.5435 | 0.5652 |
| 6 | 0.3682 | 0.3824 | 0.3729 | 0.4298 | 0.2126 | 0.2248 | 0.2019 | 0.2153 | 0.5497 | 0.5407 | 0.5258 | 0.5547 |
| 7 | 0.3682 | 0.3824 | 0.3729 | 0.4298 | 0.2035 | 0.2175 | 0.1976 | 0.2083 | 0.5433 | 0.5298 | 0.5138 | 0.5419 |
| normal_dim 256 10_Targets | normal_dim 128 10_Targets | normal_dim 64 10_Targets | normal_dim 32 10_Targets | normal_dim 256 Mnist | normal_dim 128 Mnist | normal_dim 64 Mnist | normal_dim 32 Mnist | normal_dim 256 Noisy | normal_dim 128 Noisy | normal_dim 64 Noisy | normal_dim 32 Noisy | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 0.440462 | 0.448423 | 0.437717 | 0.450613 | 0.407329 | 0.434543 | 0.55697 | 0.555693 | 0.721071 | 0.719842 | 0.71808 | 0.710819 |
| 1 | 0.491401 | 0.510573 | 0.498156 | 0.526702 | 0.420339 | 0.434074 | 0.525217 | 0.494462 | 0.748418 | 0.748178 | 0.746051 | 0.741466 |
| 2 | 0.507672 | 0.517494 | 0.508688 | 0.538066 | 0.439741 | 0.446138 | 0.516743 | 0.444587 | 0.766187 | 0.765932 | 0.764916 | 0.76216 |
| 3 | 0.510319 | 0.518058 | 0.514444 | 0.539305 | 0.457017 | 0.458949 | 0.516149 | 0.424745 | 0.778076 | 0.777833 | 0.778057 | 0.776047 |
| 4 | 0.510722 | 0.51814 | 0.515555 | 0.539533 | 0.47068 | 0.470507 | 0.519025 | 0.425091 | 0.787433 | 0.78732 | 0.788656 | 0.78689 |
| 5 | 0.510809 | 0.518149 | 0.515586 | 0.539553 | 0.482153 | 0.480636 | 0.523211 | 0.430893 | 0.795335 | 0.795433 | 0.797878 | 0.796006 |
| 6 | 0.510852 | 0.518149 | 0.515587 | 0.53956 | 0.491912 | 0.489408 | 0.528222 | 0.43841 | 0.802233 | 0.802535 | 0.806092 | 0.803902 |
| 7 | 0.510853 | 0.518149 | 0.515587 | 0.539561 | 0.500285 | 0.496997 | 0.533356 | 0.446601 | 0.808382 | 0.808806 | 0.813429 | 0.810868 |
| normal_dim 256 10_Targets | normal_dim 128 10_Targets | normal_dim 64 10_Targets | normal_dim 32 10_Targets | normal_dim 256 Mnist | normal_dim 128 Mnist | normal_dim 64 Mnist | normal_dim 32 Mnist | normal_dim 256 Noisy | normal_dim 128 Noisy | normal_dim 64 Noisy | normal_dim 32 Noisy | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 0.3092 | 0.309525 | 0.306122 | 0.313413 | 0.295574 | 0.304131 | 0.35312 | 0.347392 | 0.453886 | 0.453995 | 0.454277 | 0.451949 |
| 1 | 0.316775 | 0.323071 | 0.318368 | 0.331185 | 0.296274 | 0.297317 | 0.327295 | 0.313752 | 0.44592 | 0.446119 | 0.446861 | 0.443789 |
| 2 | 0.319462 | 0.324482 | 0.321228 | 0.33349 | 0.303093 | 0.300689 | 0.321828 | 0.288579 | 0.446974 | 0.447419 | 0.448566 | 0.445682 |
| 3 | 0.319857 | 0.324584 | 0.323429 | 0.333785 | 0.309216 | 0.305219 | 0.320593 | 0.277792 | 0.449823 | 0.450408 | 0.452136 | 0.44944 |
| 4 | 0.319921 | 0.324599 | 0.323754 | 0.333865 | 0.313521 | 0.309543 | 0.321155 | 0.276645 | 0.452979 | 0.453624 | 0.455994 | 0.453374 |
| 5 | 0.319939 | 0.324601 | 0.323765 | 0.333871 | 0.316935 | 0.313407 | 0.322482 | 0.278347 | 0.456058 | 0.456713 | 0.459779 | 0.457109 |
| 6 | 0.319943 | 0.324601 | 0.323765 | 0.333873 | 0.319834 | 0.316782 | 0.324386 | 0.281305 | 0.458959 | 0.459584 | 0.463371 | 0.460551 |
| 7 | 0.319943 | 0.324601 | 0.323765 | 0.333873 | 0.322452 | 0.319674 | 0.326474 | 0.284777 | 0.46167 | 0.462214 | 0.466714 | 0.463703 |